Data Reliability Engineer

Responsibilities

• Own and improve the reliability of data pipelines across ingestion, transformation, and delivery layers
• Establish and maintain data reliability standards including SLIs, SLOs, and SLAs
• Design and maintain monitoring, logging, and observability frameworks for data pipelines and datasets
• Implement data quality testing and validation frameworks using golden datasets and regression tests
• Lead incident response, including detection, triage, root cause analysis, and post-incident remediation
• Leverage ML and AI-assisted tools for anomaly detection, drift detection, and schema validation
• Partner with Data Engineering, DevOps, and Product teams to harden pipelines and infrastructure
• Ensure data reliability practices align with healthcare security, privacy, and compliance requirements

Requirements

• 5+ years of experience with data platforms, pipelines, or distributed data systems in production
• 1+ years of experience with machine learning-based monitoring or AI-assisted observability tools
• Proven experience improving system reliability with measurable SLI/SLO/SLA improvements
• Proficiency in Python and SQL
• Experience with cloud-based data platforms such as AWS or Databricks
• Expertise with workflow orchestration tools like Airflow or Databricks Workflows
• Strong understanding of modern data architectures and lakehouse patterns
• Bachelor's degree in Computer Science, Engineering, or a related field

Preferred Qualifications

• Experience with healthcare data standards such as FHIR, HL7, or CCD
• Hands-on experience with ML-based anomaly detection frameworks
• Experience using LLMs or AI-assisted tools like GitHub Copilot or Claude Code for development
• Experience with observability platforms like Datadog, New Relic, or PagerDuty
• Background in a startup or high-growth environment

About the Company

Vytalize Health focuses on mission-critical healthcare data, ensuring accuracy and reliability for internal and external consumers within a regulated environment.